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Optimization for Onshore Wind Farm Cable: Connection Layout using ACO-AIA algorithm

机译:陆上风电场电缆的优化:使用ACO-AIA算法的连接布局

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摘要

The wind farm layout optimization problem is similar to the classical mathematical problem of finding the Steiner Minimal Tree Problem (SMTP) of a weighted undirected graph. Due to the cable current-carrying capacity limitation, the cable sectional area should be carefully selected to meet the system operational requirement and this constraint should be considered during the SMTP formulation process. Hence, traditional SMTP algorithm cannot ensure a minimal cable investment layout. In this paper, a hybrid algorithm based on modified Ants Colony Optimization (ACO) and Artificial Immune Algorithm (AIA) for solving SMTP is introduced. Since the Steiner Tree Problem is NP-hard, we design an algorithm to construct high quality Steiner trees in a short time which is suitable for real time multicast routing in networks. After the breadth - first traversal of the minimal graph obtained by ACO, the terminal points are divided into different convex hull sets, and the full Steiner tree is structured from the convex hull sets partition. The Steiner points can then be vaccinated by AIA to get an optimal graph. The average optimization effect of AIA is shorter than the minimal graph obtained using ACO, and the performance of the algorithm is shown. We give an example of application in optimization for onshore wind farm Cable. The possibility of using different sectional area’s cable is also considered in this paper.
机译:风电场布局优化问题类似于经典数学问题,即找到加权无向图的Steiner最小树问题(SMTP)。由于电缆载流量的限制,应仔细选择电缆截面积以满足系统操作要求,并且在SMTP制定过程中应考虑此约束。因此,传统的SMTP算法无法确保最小的电缆投资布局。提出了一种基于改进蚁群算法和人工免疫算法的SMTP混合算法。由于Steiner树问题是NP难题,因此我们设计了一种算法,可以在短时间内构造高质量Steiner树,该算法适用于网络中的实时多播路由。在通过ACO获得的最小图的广度-第一次遍历之后,将端点划分为不同的凸包集,并根据凸包集划分构造整个Steiner树。然后可以通过AIA对Steiner点进行疫苗接种以获得最佳图。 AIA的平均优化效果比使用ACO获得的最小图短,并且显示了算法的性能。我们以陆上风电场电缆优化应用为例。本文还考虑了使用不同截面积电缆的可能性。

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